JP2018500080A5

JP2018500080A5 -

Info

Publication number: JP2018500080A5
Application number: JP2017529276A
Authority: JP
Filing date: 2015-12-04
Publication date: 2018-12-13
Anticipated expiration: 2035-12-04

Claims

A method of planning electrode placement to treat an epileptic seizure in a patient's brain, comprising:
Obtaining an inter-seizure profile from the brain of the patient;
Obtaining a post-stroke imaging profile from the brain of the patient;
Comparing the inter-seizure shooting profile with the post-seizure shooting profile;
Determining a seizure propagation path based on the comparison;
Determining a plurality of virtual electrode placement positions of the electrode based on the seizure propagation path;
Determining a cortical active area at each virtual electrode placement position, wherein the cortical active area at the virtual electrode placement position is based on the seizure propagation path and the virtual electrode placement position;
Selecting an implant position of the electrode from the plurality of virtual electrode placement positions, the selection being based on the cortical active region at the implant position;
A method characterized by comprising:

The method further comprises providing a plurality of energy emitting carbon nanotube transponders for delivery to the brain tissue of the patient at a location that relies on the seizure propagation path;
The method of claim 1, wherein the plurality of energy emitting carbon nanotube transponders are configured to increase the cortical active area at the implant location relative to the cortical active area of the electrode.

Obtaining an inter-seizure imaging profile comprises obtaining an inter-seizure diffusion tensor imaging MRI data set;
The method of claim 1, wherein obtaining a post-seizure imaging profile comprises obtaining a post-seizure diffusion tensor imaging MRI data set.

The step of determining the seizure propagation path includes the step of determining an anisotropy ratio in the inter-seizure diffusion tensor imaging MRI data set and the post-seizure diffusion tensor imaging MRI data set. Method.

Obtaining an inter-seizure imaging profile comprises obtaining an inter-seizure single photon emission tomography dataset;
The method of claim 1, wherein obtaining a post-seizure imaging profile comprises obtaining a post-seizure single photon emission tomography data set.

Determining cortical activation at each virtual electrode placement position comprises determining an activation function;
4. The method of claim 3, wherein determining the activation function comprises determining a potential generated by stimulation of the electrode in a homogeneous medium or an anisotropic medium.

Determining the cortical active region at each virtual electrode placement position comprises determining an activation function;
The method of claim 3, wherein determining the activation function comprises determining a potential generated by stimulation of the electrode in an anisotropic medium.

The method of claim 6, further comprising the step of determining a second-order derivation of the potential in the direction of the white matter road.

The method of claim 8, wherein the direction of the white matter tract is determined from the post-seizure diffusion tensor radiography MRI data set.

The method further comprises:
Obtaining a stimulation activated single photon emission tomography data set after applying an electrical pulse from an electrode implanted at the implant location;
Comparing the stimulus activated single photon emission tomography data set to a cortical activated region at the implant location;
Verifying the cortical activation region at the implant location based on the comparison;
The method of claim 1, comprising:

An energy emitting carbon nanotube transponder for propagating to a patient's brain tissue at a location that relies on a seizure propagation path,
The energy emitting carbon nanotube transponder is
(A) at least one carbon nanotube,
(B) a nanocapacitor connected to a first end of the at least one carbon nanotube;
With
The nanocapacitor can store a predetermined amount of electric energy and has an average charge density in the range of about 1.2 × 10 ⁻⁵ to 2.4 × 10 ⁻⁵ coulomb / cm ² . Can radiate in form,
The at least one carbon nanotube is connected to the nanocapacitor and is configured to operate as a nanoswitch that emits the predetermined amount of electric energy to the cellular tissue in accordance with an environmental change of the nanotube transponder. Has been
The carbon nanotube transponder is capable of emitting a living body non-invasive charge in the range of about 4 to about 20 microcoulombs / cm ² to the cellular tissue.

The carbon nanotube transponder according to claim 11, further comprising a coil nanowire disposed inside the nanocapacitor.

The carbon nanotube transponder according to claim 11, further comprising a coil nanowire disposed outside the nanocapacitor.

The carbon nanotube transponder according to claim 11, further comprising a biocompatible coat on an outer surface of the energy emitting carbon nanotube transponder.

The biocompatible coat is a material selected from the group comprising polylactic acid (PLA); polyglycolic acid (PGA); lactic acid-glycolic acid copolymer (PLGA); chitosan. 14. The carbon nanotube transponder according to 14.

The carbon nanotube transponder further comprises a molecular label linked to a free end of the at least one carbon nanotube;
The carbon nanotube transponder according to claim 11, wherein the free end of the carbon nanotube is an opposite end of the nanocapacitor.

The carbon nanotube transponder increases the cortical activation region at the implant position of the electrode over the cortex activation region of the electrode for treating epileptic seizures in the patient's brain. Carbon nanotube transponder.

A method of planning electrode placement to treat a tumor in a patient's brain, comprising:
Obtaining a baseline diffusion tensor radiography MRI data set from the brain of the patient;
Determining a tumor location based on the diffusion tensor imaging MRI data set;
Determining a plurality of virtual electrode placement positions based on the tumor position;
Determining a cortical activation region at each virtual electrode placement position, wherein the cortical activation region at the virtual electrode placement position is based on the tumor position and the virtual electrode placement position;
Selecting an implant position of the electrode from the plurality of virtual electrode placement positions, wherein the selection is based on the cortical activation region at the implant position;
A method characterized by comprising: